正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Still entering Excel data manually? Try this instead Select headings → Alt + D + O → OK Enter data in the form → Press Enter ✔ Faster ✔ Cleaner ✔ Time-saving Learn smart Excel tricks with #ExcelTips #Productivity #LearnExcel #ExcelTricks

Excelsirji

4,520 subscribers

36,497 次观看 • 6 个月前 •via X (Twitter)

#ExcelTips #Productivity #LearnExcel #ExcelTricks

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

The Smartest Way to Track Progress in Excel No more manual work. Just clean automation. Join for more Excel Hacks #Excel #ExcelTips #ExcelHacks #Productivity #OfficeHack #MicrosoftExcel #Automation #DataSkills #WorkSmart #DataAcademy

The Smartest Way to Track Progress in Excel No more manual work. Just clean automation. Join for more Excel Hacks #Excel #ExcelTips #ExcelHacks #Productivity #OfficeHack #MicrosoftExcel #Automation #DataSkills #WorkSmart #DataAcademy

Excelsirji

13,325 次观看 • 7 个月前

🚀 Stop Merging Data Manually in Excel! 📊 😫 Still copying and pasting data from multiple tables? There’s a smarter way. ⚡ Excel’s Consolidate feature lets you combine data from multiple ranges into a single summary in just a few clicks—saving time and reducing errors. ✅ Merge data faster ✅ Eliminate repetitive manual work ✅ Improve accuracy and productivity ✅ Perfect for reports, budgeting, and data analysis 💡 Small Excel tricks like this can save you hours over the course of a year. 📌 Save this post so you don’t forget it when working with spreadsheets! ❤️ Like • 🔄 Repost • 💬 Share with someone who still copies and pastes data manually.

🚀 Stop Merging Data Manually in Excel! 📊 😫 Still copying and pasting data from multiple tables? There’s a smarter way. ⚡ Excel’s Consolidate feature lets you combine data from multiple ranges into a single summary in just a few clicks—saving time and reducing errors. ✅ Merge data faster ✅ Eliminate repetitive manual work ✅ Improve accuracy and productivity ✅ Perfect for reports, budgeting, and data analysis 💡 Small Excel tricks like this can save you hours over the course of a year. 📌 Save this post so you don’t forget it when working with spreadsheets! ❤️ Like • 🔄 Repost • 💬 Share with someone who still copies and pastes data manually.

Tips Excel

557,801 次观看 • 1 个月前

Most CA firms are still doing GST ITC reconciliation manually… Copying data… comparing transactions… and spending hours just to find mismatches. I recently built a GST ITC Reconciliation Tool with AI to solve this exact problem. Now you can: ✔ Upload GSTR-2B ✔ Upload your books/Tally data ✔ Click once… and get a complete reconciliation summary No manual effort. No unnecessary stress. Just clean and accurate reconciliation. I’ve been using this tool myself… and it’s saving a lot of time. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below. I'll send you the details.

Most CA firms are still doing GST ITC reconciliation manually… Copying data… comparing transactions… and spending hours just to find mismatches. I recently built a GST ITC Reconciliation Tool with AI to solve this exact problem. Now you can: ✔ Upload GSTR-2B ✔ Upload your books/Tally data ✔ Click once… and get a complete reconciliation summary No manual effort. No unnecessary stress. Just clean and accurate reconciliation. I’ve been using this tool myself… and it’s saving a lot of time. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below. I'll send you the details.

Deepak Gupta

17,025 次观看 • 1 个月前

Most CA firms are still doing GST ITC reconciliation manually… Copying data… comparing transactions… and spending hours just to find mismatches. I recently built a GST ITC Reconciliation Tool with AI to solve this exact problem. Now you can: ✔ Upload GSTR-2B ✔ Upload your books/Tally data ✔ Click once… and get a complete reconciliation summary No manual effort. No unnecessary stress. Just clean and accurate reconciliation. I’ve been using this tool myself… and it’s saving a lot of time. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below I’ll send you the details.

Most CA firms are still doing GST ITC reconciliation manually… Copying data… comparing transactions… and spending hours just to find mismatches. I recently built a GST ITC Reconciliation Tool with AI to solve this exact problem. Now you can: ✔ Upload GSTR-2B ✔ Upload your books/Tally data ✔ Click once… and get a complete reconciliation summary No manual effort. No unnecessary stress. Just clean and accurate reconciliation. I’ve been using this tool myself… and it’s saving a lot of time. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below I’ll send you the details.

Deepak Gupta

44,083 次观看 • 4 个月前

GST AUTOMATION - GST Auto-Login using a Chrome Extension Stop typing GST credentials. Automate it. 🚀Advanced GST Login Automation by CA Kashish Kathuria - directly inside Chrome No Excel files to open. No repetitive typing. No switching between tools. 🔹 A custom Chrome Extension that: - Opens automatically on the GST login page - Lets you search & select a company instantly - Auto-fills the GST username - Copies the password securely (paste & go) - Leaves captcha & OTP manual — fully compliant 💡 Why this matters in 2026: ✔ CA firms handling multiple clients ✔ GST practitioners logging in dozens of times daily ✔ Compliance teams who value speed + accuracy ✔ Anyone tired of typing credentials again and again 🛠 Simple setup (no tech headache): 1️⃣ Prepare company data in a CSV 2️⃣ Install the Chrome extension 3️⃣ Open GST portal → select company → done 👇 Want access? Comment “GST AUTOMATION” here ( and send a connection request on LinkedIn ( He will share: ✔ Extension file ✔ Installation steps ✔ CSV format & best practices

GST AUTOMATION - GST Auto-Login using a Chrome Extension Stop typing GST credentials. Automate it. 🚀Advanced GST Login Automation by CA Kashish Kathuria - directly inside Chrome No Excel files to open. No repetitive typing. No switching between tools. 🔹 A custom Chrome Extension that: - Opens automatically on the GST login page - Lets you search & select a company instantly - Auto-fills the GST username - Copies the password securely (paste & go) - Leaves captcha & OTP manual — fully compliant 💡 Why this matters in 2026: ✔ CA firms handling multiple clients ✔ GST practitioners logging in dozens of times daily ✔ Compliance teams who value speed + accuracy ✔ Anyone tired of typing credentials again and again 🛠 Simple setup (no tech headache): 1️⃣ Prepare company data in a CSV 2️⃣ Install the Chrome extension 3️⃣ Open GST portal → select company → done 👇 Want access? Comment “GST AUTOMATION” here ( and send a connection request on LinkedIn ( He will share: ✔ Extension file ✔ Installation steps ✔ CSV format & best practices

Taxation Updates (CA Mayur J Sondagar)

14,884 次观看 • 6 个月前

📊 Master the TEXTSPLIT Function in Excel Still separating text manually? The TEXTSPLIT function lets you split text into multiple columns or rows instantly using a delimiter such as commas, spaces, hyphens, or other characters. Why TEXTSPLIT is Useful ✅ Clean messy datasets faster ✅ Separate names, emails, and addresses automatically ✅ Save time on repetitive text processing ✅ Improve data preparation for analysis ✅ Replace manual Text-to-Columns workflows (Save this for later).

📊 Master the TEXTSPLIT Function in Excel Still separating text manually? The TEXTSPLIT function lets you split text into multiple columns or rows instantly using a delimiter such as commas, spaces, hyphens, or other characters. Why TEXTSPLIT is Useful ✅ Clean messy datasets faster ✅ Separate names, emails, and addresses automatically ✅ Save time on repetitive text processing ✅ Improve data preparation for analysis ✅ Replace manual Text-to-Columns workflows (Save this for later).

Tips Excel

17,654 次观看 • 1 个月前

Most professionals still do bank entries manually from Excel to Tally without thinking about how much time it actually consumes. But the reality is — By doing this, a significant amount of your time gets wasted on repetitive work… and the chances of errors also increase considerably. That’s why I built a Bank Statement to Tally Automation Tool. Upload Bank Statement (Excel) Select company & bank ledger Or choose date as per your need Click once… and entries get posted automatically No hassle. No pressure. Just fast, accurate posting. ⚡ I personally use this tool regularly while handling bank entries. If you’re a CA or finance professional dealing with bulk data — this is a must-have. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below I’ll send you the details 📩

Most professionals still do bank entries manually from Excel to Tally without thinking about how much time it actually consumes. But the reality is — By doing this, a significant amount of your time gets wasted on repetitive work… and the chances of errors also increase considerably. That’s why I built a Bank Statement to Tally Automation Tool. Upload Bank Statement (Excel) Select company & bank ledger Or choose date as per your need Click once… and entries get posted automatically No hassle. No pressure. Just fast, accurate posting. ⚡ I personally use this tool regularly while handling bank entries. If you’re a CA or finance professional dealing with bulk data — this is a must-have. If you also want to automate your CA practice and learn how to build systems like this using AI… Comment your email below I’ll send you the details 📩

Deepak Gupta

17,631 次观看 • 10 天前

Copilot Tasks is seriously good?! Even one of the best alternative to Claude Cowork Using a single prompt it was able to: → Use a cloud browser to find the right tool → Interact with the page to enter data → Interpret all the info given by the page → Generate a PowerPoint based on it → Draft an email containing the learnings Because it has access in real time to multiple Microsoft Office apps like Word, PowerPoint, Excel, etc. but also Outlook. Everything was seamless. First try. And you can even ask it to schedule this task (or another one) to run it every Friday, once a month, you name it. As with OpenClaw, the use cases are basically infinite.

Copilot Tasks is seriously good?! Even one of the best alternative to Claude Cowork Using a single prompt it was able to: → Use a cloud browser to find the right tool → Interact with the page to enter data → Interpret all the info given by the page → Generate a PowerPoint based on it → Draft an email containing the learnings Because it has access in real time to multiple Microsoft Office apps like Word, PowerPoint, Excel, etc. but also Outlook. Everything was seamless. First try. And you can even ask it to schedule this task (or another one) to run it every Friday, once a month, you name it. As with OpenClaw, the use cases are basically infinite.

Paul Couvert

153,739 次观看 • 4 个月前

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi

Andrew Bolis

36,504 次观看 • 10 个月前

Still spending hours on repetitive work that should’ve been automated by now? Most teams waste valuable time creating documents from scratch, rewriting the same emails, reformatting data, and manually producing content that could be generated in seconds — with the right tools. Meet |Context — The AI Office Suite built to transform how work gets done. 🚀 Not just where you work — but what you work on. Context doesn’t just assist you. It acts like a teammate: learning, reasoning, writing, researching, and adapting to your workflow. Here’s how transforms your workday: ✅ Unified Workspace: Connect over 300 tools like Slack, Google Docs, Salesforce, and Excel in one place, and streamline your entire workflow. ✅ AI-Powered Automation: Let AI handle repetitive tasks, generate content, and update documents in real time, saving you hours every week. ✅ Real-Time Collaboration: Collaborate seamlessly with your team on shared workspaces, making edits, updates, and feedback simple and quick. ✅ Top-Tier Security: With enterprise-grade security, including SOC 2, GDPR compliance, and AES-256 encryption, your data stays safe and secure. ✅ Endless Customization: Build custom templates, automate research, and tailor workflows to meet the unique needs of your business. Ready to level up your workflow? Try it now👉 #ContextAI #Automation #AIWorkspace #Productivity #SmartWork #NoCodeTools #AIIntegration #Teamworkrder

Still spending hours on repetitive work that should’ve been automated by now? Most teams waste valuable time creating documents from scratch, rewriting the same emails, reformatting data, and manually producing content that could be generated in seconds — with the right tools. Meet |Context — The AI Office Suite built to transform how work gets done. 🚀 Not just where you work — but what you work on. Context doesn’t just assist you. It acts like a teammate: learning, reasoning, writing, researching, and adapting to your workflow. Here’s how transforms your workday: ✅ Unified Workspace: Connect over 300 tools like Slack, Google Docs, Salesforce, and Excel in one place, and streamline your entire workflow. ✅ AI-Powered Automation: Let AI handle repetitive tasks, generate content, and update documents in real time, saving you hours every week. ✅ Real-Time Collaboration: Collaborate seamlessly with your team on shared workspaces, making edits, updates, and feedback simple and quick. ✅ Top-Tier Security: With enterprise-grade security, including SOC 2, GDPR compliance, and AES-256 encryption, your data stays safe and secure. ✅ Endless Customization: Build custom templates, automate research, and tailor workflows to meet the unique needs of your business. Ready to level up your workflow? Try it now👉 #ContextAI #Automation #AIWorkspace #Productivity #SmartWork #NoCodeTools #AIIntegration #Teamworkrder

Manish Kumar Shah

33,734 次观看 • 1 年前

The COVID Cover-Up Crumbles—But the Assault on Children Continues 🚨 Pfizer wanted to hide its clinical trial data for 75 YEARS. Let that sink in. 75 years of buried adverse events, suppressed science, and undisclosed risks—all while governments & health agencies pushed their shots onto billions. Now, thanks to relentless pressure from journalists, lawsuits, and the House Select Subcommittee on the Coronavirus Pandemic, the truth is finally emerging. And it’s damning. Dr. Brian Hooker warns: "The FDA, CDC, and NIH have been captured by Pharma. They fast-tracked vaccines with minimal safety testing, ignored red flags, and now they’re injecting BABIES with a shot that doesn’t even have full approval—just Emergency Use Authorization. This isn’t science. It’s an experiment." The Greatest Medical Scandal of Our Time - Pfizer’s own documents reveal thousands of adverse events, yet regulators looked the other way. - Healthy children face near-zero risk from COVID, but the CDC added the shot to the infant vaccine schedule anyway. - Myocarditis, neurological events, and immune dysfunction were downplayed—while dissenters were silenced. Who’s Protecting Our Kids? The same agencies that: ✔ Ridiculed natural immunity ✔ Censored doctors ✔ Pushed boosters with zero long-term safety data …are now pressuring parents to jab their babies for a virus that poses less risk than the flu. This isn’t public health. It’s profit-driven malpractice. The Fight Isn’t Over The walls are closing in on the COVID industrial complex. More whistleblowers are stepping forward. More data is leaking. More politicians are demanding answers. But until we have: ✅ Full transparency ✅ Criminal accountability ✅ An end to Pharma’s stranglehold on regulators …the war on medical freedom continues. Share this. Expose the truth. Hold them accountable.

The COVID Cover-Up Crumbles—But the Assault on Children Continues 🚨 Pfizer wanted to hide its clinical trial data for 75 YEARS. Let that sink in. 75 years of buried adverse events, suppressed science, and undisclosed risks—all while governments & health agencies pushed their shots onto billions. Now, thanks to relentless pressure from journalists, lawsuits, and the House Select Subcommittee on the Coronavirus Pandemic, the truth is finally emerging. And it’s damning. Dr. Brian Hooker warns: "The FDA, CDC, and NIH have been captured by Pharma. They fast-tracked vaccines with minimal safety testing, ignored red flags, and now they’re injecting BABIES with a shot that doesn’t even have full approval—just Emergency Use Authorization. This isn’t science. It’s an experiment." The Greatest Medical Scandal of Our Time - Pfizer’s own documents reveal thousands of adverse events, yet regulators looked the other way. - Healthy children face near-zero risk from COVID, but the CDC added the shot to the infant vaccine schedule anyway. - Myocarditis, neurological events, and immune dysfunction were downplayed—while dissenters were silenced. Who’s Protecting Our Kids? The same agencies that: ✔ Ridiculed natural immunity ✔ Censored doctors ✔ Pushed boosters with zero long-term safety data …are now pressuring parents to jab their babies for a virus that poses less risk than the flu. This isn’t public health. It’s profit-driven malpractice. The Fight Isn’t Over The walls are closing in on the COVID industrial complex. More whistleblowers are stepping forward. More data is leaking. More politicians are demanding answers. But until we have: ✅ Full transparency ✅ Criminal accountability ✅ An end to Pharma’s stranglehold on regulators …the war on medical freedom continues. Share this. Expose the truth. Hold them accountable.

Camus

13,178 次观看 • 11 个月前

Forget about complicated Excel formulas. Leave it in 2008. Using this AI platform, you can create presentations with interactive charts just by using a prompt. Here is how you can turn any data into beautiful visual presentations: Gamma — the all-in-one platform to create social media posts, presentations, landing pages, and documents in less than a minute using AI. Forget about manually designing; this tool is a game changer. Let me show you how it works in action: I went to [ and I asked it: "Create a presentation with charts showing New York immigration data and its impact on music culture" In less than a minute, Gamma created an 8-page beautifully looking presentation. It works especially for people who need to present ideas fast and do not have time. Literally prompt and watch it cook. Not only that, it also broke down the immigration population by division percentage. So it's not only making the presentations look good but also making them practical. Over 50 million users are using Gamma every day to be 1% better at their work. And if you're still not on board, now is your time. Give Gamma a try for free today:

Forget about complicated Excel formulas. Leave it in 2008. Using this AI platform, you can create presentations with interactive charts just by using a prompt. Here is how you can turn any data into beautiful visual presentations: Gamma — the all-in-one platform to create social media posts, presentations, landing pages, and documents in less than a minute using AI. Forget about manually designing; this tool is a game changer. Let me show you how it works in action: I went to [ and I asked it: "Create a presentation with charts showing New York immigration data and its impact on music culture" In less than a minute, Gamma created an 8-page beautifully looking presentation. It works especially for people who need to present ideas fast and do not have time. Literally prompt and watch it cook. Not only that, it also broke down the immigration population by division percentage. So it's not only making the presentations look good but also making them practical. Over 50 million users are using Gamma every day to be 1% better at their work. And if you're still not on board, now is your time. Give Gamma a try for free today:

Alif Hossain

34,541 次观看 • 11 个月前

PhD Students – How to extract data from papers for your literature review in seconds? Extracting data from papers takes a lot of time. You can automate this process with Bohrium 𝐇𝐨𝐰 𝐭𝐨 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐜𝐚𝐥𝐥𝐲 𝐞𝐱𝐭𝐫𝐚𝐜𝐭 𝐝𝐚𝐭𝐚 𝐟𝐫𝐨𝐦 𝐩𝐚𝐩𝐞𝐫𝐬? 1. Go to and log in 2. Click on 𝐾𝑛𝑜𝑤𝑙𝑒𝑑𝑔𝑒 𝐵𝑎𝑠𝑒 from the left menu 3. Upload the papers you selected for literature review 4. You will see the following option against each paper - Read PDF - Key Takeaway - AI Poster 5. Click on 𝑅𝑒𝑎𝑑 𝑃𝐷𝐹 for the first paper in your list 6. Write a prompt for the data you want to extract 7. For example, you can enter datasets, methodology etc. 8. It will extract the required data from the paper 9. If you want to extract Key Takeaways from the paper 10. Go back and click on 𝐾𝑒𝑦 𝑇𝑎𝑘𝑒𝑎𝑤𝑎𝑦𝑠 11. Bohrium will extract Key Takeaways from the paper 12. In addition to this, you also have 2 more options - AI Poster - Podcast 13. Click on 𝐴𝐼 𝑃𝑜𝑠𝑡𝑒𝑟 and it will create a poster for you 14. This is the poster based on the given research paper 15. If you click on 𝑃𝑜𝑑𝑐𝑎𝑠𝑡, it will convert the paper to audio 16. You can listen to the paper instead of reading it Repeat this cycle for all the papers in your pool. You will end up with the required data. You can use this data to write your literature review Try Bohrium today for FREE: Anything you’d like to add?

PhD Students – How to extract data from papers for your literature review in seconds? Extracting data from papers takes a lot of time. You can automate this process with Bohrium 𝐇𝐨𝐰 𝐭𝐨 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐜𝐚𝐥𝐥𝐲 𝐞𝐱𝐭𝐫𝐚𝐜𝐭 𝐝𝐚𝐭𝐚 𝐟𝐫𝐨𝐦 𝐩𝐚𝐩𝐞𝐫𝐬? 1. Go to and log in 2. Click on 𝐾𝑛𝑜𝑤𝑙𝑒𝑑𝑔𝑒 𝐵𝑎𝑠𝑒 from the left menu 3. Upload the papers you selected for literature review 4. You will see the following option against each paper - Read PDF - Key Takeaway - AI Poster 5. Click on 𝑅𝑒𝑎𝑑 𝑃𝐷𝐹 for the first paper in your list 6. Write a prompt for the data you want to extract 7. For example, you can enter datasets, methodology etc. 8. It will extract the required data from the paper 9. If you want to extract Key Takeaways from the paper 10. Go back and click on 𝐾𝑒𝑦 𝑇𝑎𝑘𝑒𝑎𝑤𝑎𝑦𝑠 11. Bohrium will extract Key Takeaways from the paper 12. In addition to this, you also have 2 more options - AI Poster - Podcast 13. Click on 𝐴𝐼 𝑃𝑜𝑠𝑡𝑒𝑟 and it will create a poster for you 14. This is the poster based on the given research paper 15. If you click on 𝑃𝑜𝑑𝑐𝑎𝑠𝑡, it will convert the paper to audio 16. You can listen to the paper instead of reading it Repeat this cycle for all the papers in your pool. You will end up with the required data. You can use this data to write your literature review Try Bohrium today for FREE: Anything you’d like to add?

Faheem Ullah

13,413 次观看 • 10 个月前

We’re building in public 👀 Check out our NEW platform demo, delivering upgraded features from the moment you enter. This version gives you a faster, clearer, more responsive interface designed to help you act on real conviction, not delayed noise. Featuring: 🔸 Real time signals and sentiment layers 🔸 NodePulse, a live intelligence feed scanning 600+ data sources for breaking market events 🔸 Creator tools allowing you to generate signals for new rewards 🔸 Community voting on popular signals 🔸 Profile tools, upgrades, and contribution tracking Every part of V2 reflects the mission of Nodepay: turning collective human activity into structured, real time intelligence. → You get clearer context, stronger signals, and a platform that moves with the market instead of behind it. Tester selection starts this week. Join our discord now:

Nodepay

118,704 次观看 • 7 个月前

Use this FREE tool to generate the first draft of ANY type of literature review. Meet AnswerThis — a tool that makes literature review faster and easier. Here’s how it works. 1. Visit and log in. 2. Select the 𝐿𝑖𝑡𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑅𝑒𝑣𝑖𝑒𝑤 option from the menu. 3. From the prompt helper, select 𝑊𝑟𝑖𝑡𝑒 𝑎 𝑙𝑖𝑡𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑟𝑒𝑣𝑖𝑒𝑤 𝑜𝑛. 4. Enter your research topic in the blank text field ➝ For example, Vulnerabilities in Big Data Systems 5. Click 𝐶𝑟𝑒𝑎𝑡𝑒 to generate the initial search prompt. 6. Press Enter to see research filter options. 7. Choose your response type based on your needs. ➝ Structured Literature Review: Citation-rich and detailed. ➝ Dynamic Research Assistant: To explore research gaps. ➝ AI Only: Fast, but unreliable with no citations. 8. Set the minimum number of citations for the review. ➝ Choose at least 10 for comprehensive results. 9. Decide whether to enable 𝑇𝑢𝑟𝑏𝑜 𝑀𝑜𝑑𝑒 for faster results. ➝ Disabling it gives you more comprehensive answers. 10. Select the sources for search results. ➝ Choose both web and databases for thorough results. 11. Specify the date range to get recent papers. 12. Enable 𝑑𝑜𝑢𝑏𝑙𝑒-𝑐ℎ𝑒𝑐𝑘 𝑐𝑖𝑡𝑎𝑡𝑖𝑜𝑛𝑠 for accurate results. 13. Once filters are set, click 𝑆𝑢𝑏𝑚𝑖𝑡 𝑆𝑒𝑎𝑟𝑐ℎ to proceed. 14. After a while, your literature review will be generated. ➝ Sources and citations will be listed on the right. 15. Review the results and assess the paper sources carefully. 16. Add relevant papers to your library for easy access later. 17. Export citations in formats like BibTeX or CSV as needed. 18. You can also download the review as a Word or PDF file. Treat this literature review as an initial draft. Refine it and build your review on the top of it. Ready to make literature review effortless? Try AnswerThis ( today and see the difference!

Use this FREE tool to generate the first draft of ANY type of literature review. Meet AnswerThis — a tool that makes literature review faster and easier. Here’s how it works. 1. Visit and log in. 2. Select the 𝐿𝑖𝑡𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑅𝑒𝑣𝑖𝑒𝑤 option from the menu. 3. From the prompt helper, select 𝑊𝑟𝑖𝑡𝑒 𝑎 𝑙𝑖𝑡𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑟𝑒𝑣𝑖𝑒𝑤 𝑜𝑛. 4. Enter your research topic in the blank text field ➝ For example, Vulnerabilities in Big Data Systems 5. Click 𝐶𝑟𝑒𝑎𝑡𝑒 to generate the initial search prompt. 6. Press Enter to see research filter options. 7. Choose your response type based on your needs. ➝ Structured Literature Review: Citation-rich and detailed. ➝ Dynamic Research Assistant: To explore research gaps. ➝ AI Only: Fast, but unreliable with no citations. 8. Set the minimum number of citations for the review. ➝ Choose at least 10 for comprehensive results. 9. Decide whether to enable 𝑇𝑢𝑟𝑏𝑜 𝑀𝑜𝑑𝑒 for faster results. ➝ Disabling it gives you more comprehensive answers. 10. Select the sources for search results. ➝ Choose both web and databases for thorough results. 11. Specify the date range to get recent papers. 12. Enable 𝑑𝑜𝑢𝑏𝑙𝑒-𝑐ℎ𝑒𝑐𝑘 𝑐𝑖𝑡𝑎𝑡𝑖𝑜𝑛𝑠 for accurate results. 13. Once filters are set, click 𝑆𝑢𝑏𝑚𝑖𝑡 𝑆𝑒𝑎𝑟𝑐ℎ to proceed. 14. After a while, your literature review will be generated. ➝ Sources and citations will be listed on the right. 15. Review the results and assess the paper sources carefully. 16. Add relevant papers to your library for easy access later. 17. Export citations in formats like BibTeX or CSV as needed. 18. You can also download the review as a Word or PDF file. Treat this literature review as an initial draft. Refine it and build your review on the top of it. Ready to make literature review effortless? Try AnswerThis ( today and see the difference!

Faheem Ullah

12,694 次观看 • 6 个月前

🚨 ALERT FLORIDA & AMERICA 🚨 The Muslim Brotherhood Infrastructure Exposed by an Undercover Journalist a Decade Ago Is Now Fully Operational in Your State. Nearly ten years ago, journalist and counter-terrorism expert Tsvi Yehezkeli went undercover inside the Muslim Brotherhood’s network in America. Speaking perfect Arabic, posing as a Palestinian, he slipped into CAIR offices, mosques tied to Anwar al-Awlaki, Brotherhood-linked charities, prison recruitment hubs, and political influence centers across the United States - including Florida. One of the central features of his investigation was CAIR Florida, where Yehezkeli met with director Hassan Shibly, who openly described how American freedoms and the U.S. Constitution benefit Islam and protect their agenda. Shibly even said plainly: “Praise Allah, the thing that helps us the most is the American Constitution.” “Democracy in America benefits Islam very much.” These were not slips - they were admissions. What Yehezkeli exposed back then should have been a five-alarm national emergency: ✔ CAIR praised the U.S. Constitution as the tool that “helps them the most,” openly acknowledging that American law protects and advances their Islamic agenda. ✔ Brotherhood leaders declared America would “become an Islamic country.” ✔ Children in U.S. mosques were taught “Jihad is good.” ✔ Prisons were mass-conversion and recruitment factories. ✔ Da’wa (Islamic ideological expansion) was described as the #1 weapon. ✔ “Moderate” leaders who smiled for English-speaking media preached Sharia supremacy and conquest in Arabic. 🔺And remember — this was 2016–2017. Since then? The network has not merely grown —it has multiplied. The institutions he infiltrated have not weakened — they have matured. The movement he exposed has not hidden — it has embedded itself into American life. Just look at Florida today: Florida is now home to: One of the largest and most politically aggressive CAIR operations in the entire country Sprawling mosque and school complexes tied to foreign ideological networks Muslim Brotherhood-aligned activists embedded in government and law enforcement outreach A booming prison-to-mosque pipeline Youth indoctrination models imported directly from Brotherhood structures abroad Political operations built on religious bloc-voting and intimidation Everything Yehezkeli documented in its early stages has now rooted itself deeply inside Florida’s infrastructure. 🚨Yehezkeli documented the opening phase. America is now living in the expansion phase. He warned that the Brotherhood wages a “quiet jihad”, entering elections, wearing suits and ties, presenting themselves as moderates, while preaching Islamic supremacy behind closed doors. Western leaders ignored him. Instead, they allowed the very same Brotherhood-linked groups to smear anyone who sounded the alarm as “Islamophobic.” But nearly a decade later? Everything he documented is now: 🔥 Mainstream 🔥 Normalized 🔥 Institutionalized 🔥 Operating in broad daylight Exactly as the Brotherhood planned. THE ONLY QUESTION LEFT: 🔥 Does America realize how deeply the Brotherhood has already embedded itself into this country? 🔥 And does Florida understand what’s been built inside its borders — right under its leaders’ noses? Tsvi Yehezkeli tried to warn us when there was still time. Now the clock is running out. BAN THE MUSLIM BROTHERHOOD - BAN CAIR See the full report and full videos:

🚨 ALERT FLORIDA & AMERICA 🚨 The Muslim Brotherhood Infrastructure Exposed by an Undercover Journalist a Decade Ago Is Now Fully Operational in Your State. Nearly ten years ago, journalist and counter-terrorism expert Tsvi Yehezkeli went undercover inside the Muslim Brotherhood’s network in America. Speaking perfect Arabic, posing as a Palestinian, he slipped into CAIR offices, mosques tied to Anwar al-Awlaki, Brotherhood-linked charities, prison recruitment hubs, and political influence centers across the United States - including Florida. One of the central features of his investigation was CAIR Florida, where Yehezkeli met with director Hassan Shibly, who openly described how American freedoms and the U.S. Constitution benefit Islam and protect their agenda. Shibly even said plainly: “Praise Allah, the thing that helps us the most is the American Constitution.” “Democracy in America benefits Islam very much.” These were not slips - they were admissions. What Yehezkeli exposed back then should have been a five-alarm national emergency: ✔ CAIR praised the U.S. Constitution as the tool that “helps them the most,” openly acknowledging that American law protects and advances their Islamic agenda. ✔ Brotherhood leaders declared America would “become an Islamic country.” ✔ Children in U.S. mosques were taught “Jihad is good.” ✔ Prisons were mass-conversion and recruitment factories. ✔ Da’wa (Islamic ideological expansion) was described as the #1 weapon. ✔ “Moderate” leaders who smiled for English-speaking media preached Sharia supremacy and conquest in Arabic. 🔺And remember — this was 2016–2017. Since then? The network has not merely grown —it has multiplied. The institutions he infiltrated have not weakened — they have matured. The movement he exposed has not hidden — it has embedded itself into American life. Just look at Florida today: Florida is now home to: One of the largest and most politically aggressive CAIR operations in the entire country Sprawling mosque and school complexes tied to foreign ideological networks Muslim Brotherhood-aligned activists embedded in government and law enforcement outreach A booming prison-to-mosque pipeline Youth indoctrination models imported directly from Brotherhood structures abroad Political operations built on religious bloc-voting and intimidation Everything Yehezkeli documented in its early stages has now rooted itself deeply inside Florida’s infrastructure. 🚨Yehezkeli documented the opening phase. America is now living in the expansion phase. He warned that the Brotherhood wages a “quiet jihad”, entering elections, wearing suits and ties, presenting themselves as moderates, while preaching Islamic supremacy behind closed doors. Western leaders ignored him. Instead, they allowed the very same Brotherhood-linked groups to smear anyone who sounded the alarm as “Islamophobic.” But nearly a decade later? Everything he documented is now: 🔥 Mainstream 🔥 Normalized 🔥 Institutionalized 🔥 Operating in broad daylight Exactly as the Brotherhood planned. THE ONLY QUESTION LEFT: 🔥 Does America realize how deeply the Brotherhood has already embedded itself into this country? 🔥 And does Florida understand what’s been built inside its borders — right under its leaders’ noses? Tsvi Yehezkeli tried to warn us when there was still time. Now the clock is running out. BAN THE MUSLIM BROTHERHOOD - BAN CAIR See the full report and full videos:

Amy Mek

89,497 次观看 • 8 个月前

🚨 ALERT AMERICA: HERE IS THE PROOF - ONE OF THE NINE FEDERAL REFUGEE CONTRACTORS ADMITTED THE ENTIRE RESETTLEMENT SCHEME ON CAMERA AMERICA HAS BEEN SOLD OUT! This 2021 video from Episcopal Migration Ministries (EMM), one of the nine federally funded refugee resettlement contractors, is one of the most revealing pieces of footage you will see. They were speaking openly at All Saints Church in Pasadena, assuming no one outside their activist circles was paying attention. But what they admitted is devastating. This wasn’t a sermon or charity. It was a full-blown political strategy briefing, filmed in a church, explaining how the U.S. government and religious NGOs work together to: 📍 dramatically expand resettlement pipelines 📍 pressure Congress to change immigration laws 📍 mobilize churches as pro-immigration activist armies 📍 build permanent support networks for arrivals 📍 redefine “refugee” to include economic & climate migrants 📍 overload the system by design 📍 coordinate lobbying directly with Washington And they said all of it out loud - we are funding our own demise! 1. They admit they are an official U.S. government partner Brother Chris McNabb of EMM states: “EMM is a ministry of the Episcopal Church and one of nine national agencies responsible for resettling refugees in the United States in partnership with the government.” This is not charity. They are federal contractors with a financial quota. More refugees = more money. It’s that simple. This is state-funded demographic policy laundered through churches. 2. They confessed the scale: from 18,000 refugees → to 4,000 Afghans PER WEEK McNabb brags: “In 2020 all nine agencies resettled about 18,000 refugees. We are now resettling 4,000 Afghans a week.” This was a mass importation pipeline, not a humanitarian drip. He openly says they had to “staff up significantly” because the pipeline “exploded overnight.” 3. They admit DHS used “humanitarian parole” to bypass the legal process McNabb explains Afghans were: “Paroled in by the Department of Homeland Security… because they did not have time to wait for the immigration system to operate.” Translation: ➡ Normal vetting was bypassed. ➡ The legal process was circumvented. ➡ Tens of thousands were rushed in without proper screening. Congress still hasn’t adjusted their status, but the arrivals are here permanently. 4. They train congregations to take in asylum seekers and parolees — not just refugees Through the Neighbor to Neighbor program, churches are trained to: 📍 provide physical & emotional support 📍 provide transportation 📍 help navigate legal processes 📍 sponsor asylum seekers & Afghan parolees Teams of 5–10 church members take over the roles official agencies would normally handle. This decentralizes the pipeline and embeds it inside communities. 5. They push churches to DEFUND ICE Rector Mike Kinman proudly declares: “We are strong advocates for the complete defunding of ICE.” So you have: 📍 a federally connected resettlement contractor 📍 working with the State Department 📍 using a church pulpit to demand the abolition of ICE This isn’t ministry. This is open-borders political warfare. 6. They openly plan to expand “refugee” to include climate & economic migrants When asked what happens to migrants who don’t meet asylum criteria, McNabb says: “We will begin seeing more and more climate refugees… more folks who come for economic reasons. We are preparing for that.” They are planning the next wave, economic & climate migrants, long before Congress approves anything. 7. They reveal the Episcopal Church has a lobbying arm on Capitol Hill They talk about OGR - the Office of Government Relations - their official lobbying office in the “God Box” on Capitol Hill. From the stage they instruct congregants to: 📍 call Congress 📍 pressure senators 📍 demand the Afghan Adjustment Act 📍 expand asylum categories 📍 increase refugee admissions 📍 secure more funding for EMM This is organized political lobbying coordinated from the church pews. 8. They admit they operate 11 affiliate offices nationwide, including in red states When asked about IRIS in Los Angeles, McNabb says: “That’s one of our 11 affiliates.” They place arrivals everywhere: Los Angeles, Seattle, Austin, Miami, and beyond. Red states are the main prize. And their “interfaith” branding? A manipulative façade - a left-wing coalition built to push anti-Western, anti-Christian, and anti-Jewish policy through religious cover. 9. They tell congregations to serve undocumented immigrants, too Kinman boasts All Saints is a “sanctuary church” ready to support: 📍 undocumented immigrants 📍 asylum seekers 📍 Afghan parolees 📍 migrants with “various statuses” This goes far beyond refugees — this is a parallel, extra-legal system. 10. They end by admitting the goal is a permanent, embedded migration infrastructure McNabb says this is just: “the beginning of a relationship.” The goal is permanent community integration — meaning once these pipelines enter your town, they never leave. 🚨 WHY THIS MATTERS, AMERICA This is just ONE of the nine federal contractors. In one hour, at one church, they admitted: ✔ their formal partnership with the U.S. government ✔ the massive scale of Afghan importation ✔ bypassing normal processes through parole ✔ pushing to abolish ICE ✔ expansion to climate & economic migrants ✔ their professional lobbying arm ✔ their nationwide network ✔ their plan for permanent demographic restructuring If this is what they say on camera, imagine what they say off camera. Americans deserve to see this video, understand how this system truly works, and decide whether they consent to having their communities transformed, with their tax dollars, without their input. Any politician - Republican or Democrat - who continues funding this racket, this federally backed demographic-engineering pipeline that European leaders openly describe as human-trafficker behavior — WILL be held accountable. If you fund it, defend it, or stay silent while your voters are kept in the dark, Laura Loomer and I will expose you. And WE will fight with everything we have to make sure you never hold office again. No one is going to fight like Laura and me to protect American communities from turning into mini-Islamic states!

🚨 ALERT AMERICA: HERE IS THE PROOF - ONE OF THE NINE FEDERAL REFUGEE CONTRACTORS ADMITTED THE ENTIRE RESETTLEMENT SCHEME ON CAMERA AMERICA HAS BEEN SOLD OUT! This 2021 video from Episcopal Migration Ministries (EMM), one of the nine federally funded refugee resettlement contractors, is one of the most revealing pieces of footage you will see. They were speaking openly at All Saints Church in Pasadena, assuming no one outside their activist circles was paying attention. But what they admitted is devastating. This wasn’t a sermon or charity. It was a full-blown political strategy briefing, filmed in a church, explaining how the U.S. government and religious NGOs work together to: 📍 dramatically expand resettlement pipelines 📍 pressure Congress to change immigration laws 📍 mobilize churches as pro-immigration activist armies 📍 build permanent support networks for arrivals 📍 redefine “refugee” to include economic & climate migrants 📍 overload the system by design 📍 coordinate lobbying directly with Washington And they said all of it out loud - we are funding our own demise! 1. They admit they are an official U.S. government partner Brother Chris McNabb of EMM states: “EMM is a ministry of the Episcopal Church and one of nine national agencies responsible for resettling refugees in the United States in partnership with the government.” This is not charity. They are federal contractors with a financial quota. More refugees = more money. It’s that simple. This is state-funded demographic policy laundered through churches. 2. They confessed the scale: from 18,000 refugees → to 4,000 Afghans PER WEEK McNabb brags: “In 2020 all nine agencies resettled about 18,000 refugees. We are now resettling 4,000 Afghans a week.” This was a mass importation pipeline, not a humanitarian drip. He openly says they had to “staff up significantly” because the pipeline “exploded overnight.” 3. They admit DHS used “humanitarian parole” to bypass the legal process McNabb explains Afghans were: “Paroled in by the Department of Homeland Security… because they did not have time to wait for the immigration system to operate.” Translation: ➡ Normal vetting was bypassed. ➡ The legal process was circumvented. ➡ Tens of thousands were rushed in without proper screening. Congress still hasn’t adjusted their status, but the arrivals are here permanently. 4. They train congregations to take in asylum seekers and parolees — not just refugees Through the Neighbor to Neighbor program, churches are trained to: 📍 provide physical & emotional support 📍 provide transportation 📍 help navigate legal processes 📍 sponsor asylum seekers & Afghan parolees Teams of 5–10 church members take over the roles official agencies would normally handle. This decentralizes the pipeline and embeds it inside communities. 5. They push churches to DEFUND ICE Rector Mike Kinman proudly declares: “We are strong advocates for the complete defunding of ICE.” So you have: 📍 a federally connected resettlement contractor 📍 working with the State Department 📍 using a church pulpit to demand the abolition of ICE This isn’t ministry. This is open-borders political warfare. 6. They openly plan to expand “refugee” to include climate & economic migrants When asked what happens to migrants who don’t meet asylum criteria, McNabb says: “We will begin seeing more and more climate refugees… more folks who come for economic reasons. We are preparing for that.” They are planning the next wave, economic & climate migrants, long before Congress approves anything. 7. They reveal the Episcopal Church has a lobbying arm on Capitol Hill They talk about OGR - the Office of Government Relations - their official lobbying office in the “God Box” on Capitol Hill. From the stage they instruct congregants to: 📍 call Congress 📍 pressure senators 📍 demand the Afghan Adjustment Act 📍 expand asylum categories 📍 increase refugee admissions 📍 secure more funding for EMM This is organized political lobbying coordinated from the church pews. 8. They admit they operate 11 affiliate offices nationwide, including in red states When asked about IRIS in Los Angeles, McNabb says: “That’s one of our 11 affiliates.” They place arrivals everywhere: Los Angeles, Seattle, Austin, Miami, and beyond. Red states are the main prize. And their “interfaith” branding? A manipulative façade - a left-wing coalition built to push anti-Western, anti-Christian, and anti-Jewish policy through religious cover. 9. They tell congregations to serve undocumented immigrants, too Kinman boasts All Saints is a “sanctuary church” ready to support: 📍 undocumented immigrants 📍 asylum seekers 📍 Afghan parolees 📍 migrants with “various statuses” This goes far beyond refugees — this is a parallel, extra-legal system. 10. They end by admitting the goal is a permanent, embedded migration infrastructure McNabb says this is just: “the beginning of a relationship.” The goal is permanent community integration — meaning once these pipelines enter your town, they never leave. 🚨 WHY THIS MATTERS, AMERICA This is just ONE of the nine federal contractors. In one hour, at one church, they admitted: ✔ their formal partnership with the U.S. government ✔ the massive scale of Afghan importation ✔ bypassing normal processes through parole ✔ pushing to abolish ICE ✔ expansion to climate & economic migrants ✔ their professional lobbying arm ✔ their nationwide network ✔ their plan for permanent demographic restructuring If this is what they say on camera, imagine what they say off camera. Americans deserve to see this video, understand how this system truly works, and decide whether they consent to having their communities transformed, with their tax dollars, without their input. Any politician - Republican or Democrat - who continues funding this racket, this federally backed demographic-engineering pipeline that European leaders openly describe as human-trafficker behavior — WILL be held accountable. If you fund it, defend it, or stay silent while your voters are kept in the dark, Laura Loomer and I will expose you. And WE will fight with everything we have to make sure you never hold office again. No one is going to fight like Laura and me to protect American communities from turning into mini-Islamic states!

Amy Mek

229,978 次观看 • 7 个月前

Everyone is sleeping on Meta's SAM 3 release. But it's actually a big deal. Here's why: Companies spend millions paying humans to label images and videos frame by frame. A single autonomous driving dataset? Months of work, hundreds of annotators, millions in cost. Without labeled data, you can't train custom models. Without custom models, you're stuck with generic solutions. This is why most companies never move past pilots. SAM 3 breaks this cycle. First let's look at the evolution: SAM 1 segmented objects when you clicked on them. Revolutionary, but one object at a time. SAM 2 added video tracking with memory. Game-changing, but you still manually prompted every object. SAM 3 changes everything with text prompts. Type "yellow school bus" and it finds ALL of them in your image or video. Not just one. Every instance across thousands of frames. Now here's where people get confused: "Can't I just use GPT-5 or Gemini for this?" No, and here's why that's a terrible approach. Large multimodal LLMs are great for reasoning, but they're slow and expensive for production visual tasks. You're paying API costs per image, waiting seconds for responses, getting inconsistent results. SAM 3 runs in 30 milliseconds on a single GPU for 100+ objects. That's 100x faster, and you own the infrastructure. More importantly, SAM 3 gives you precise pixel-level masks, not descriptions. Try asking an LLM to segment every defective part on a manufacturing line in real-time. It won't work. SAM 3 does this effortlessly. The real breakthrough is their data engine. Meta built an AI-human hybrid system that's 5x faster for complex annotations. They trained SAM 3 on 4 million unique visual concepts - 50x more than existing benchmarks like LVIS. SAM 3 is trained on 4 million unique visual concepts, it handles everything: - Text-based concept search - Interactive refinement with clicks - Video tracking across frames - Zero-shot detection of new concepts The model is open source. Weights, code, and benchmarks are on GitHub. If you're building computer vision applications, this is the foundation model to evaluate. The annotation time savings alone will pay for integration costs within weeks. Find the relevant links in the next tweet!

Everyone is sleeping on Meta's SAM 3 release. But it's actually a big deal. Here's why: Companies spend millions paying humans to label images and videos frame by frame. A single autonomous driving dataset? Months of work, hundreds of annotators, millions in cost. Without labeled data, you can't train custom models. Without custom models, you're stuck with generic solutions. This is why most companies never move past pilots. SAM 3 breaks this cycle. First let's look at the evolution: SAM 1 segmented objects when you clicked on them. Revolutionary, but one object at a time. SAM 2 added video tracking with memory. Game-changing, but you still manually prompted every object. SAM 3 changes everything with text prompts. Type "yellow school bus" and it finds ALL of them in your image or video. Not just one. Every instance across thousands of frames. Now here's where people get confused: "Can't I just use GPT-5 or Gemini for this?" No, and here's why that's a terrible approach. Large multimodal LLMs are great for reasoning, but they're slow and expensive for production visual tasks. You're paying API costs per image, waiting seconds for responses, getting inconsistent results. SAM 3 runs in 30 milliseconds on a single GPU for 100+ objects. That's 100x faster, and you own the infrastructure. More importantly, SAM 3 gives you precise pixel-level masks, not descriptions. Try asking an LLM to segment every defective part on a manufacturing line in real-time. It won't work. SAM 3 does this effortlessly. The real breakthrough is their data engine. Meta built an AI-human hybrid system that's 5x faster for complex annotations. They trained SAM 3 on 4 million unique visual concepts - 50x more than existing benchmarks like LVIS. SAM 3 is trained on 4 million unique visual concepts, it handles everything: - Text-based concept search - Interactive refinement with clicks - Video tracking across frames - Zero-shot detection of new concepts The model is open source. Weights, code, and benchmarks are on GitHub. If you're building computer vision applications, this is the foundation model to evaluate. The annotation time savings alone will pay for integration costs within weeks. Find the relevant links in the next tweet!

Akshay 🚀

46,404 次观看 • 8 个月前

🚀 Three Next-Gen AI & Web3 Projects Are Launching on Mindo AI A new chapter for community-powered intelligence, prediction markets, and open AI infrastructure The AI + Web3 landscape is entering a decisive phase — one where real usage, real revenue, and real ownership matter more than hype. Today, MindoAI is proud to welcome three groundbreaking projects that represent this shift clearly and powerfully: Perceptron Network Space DeepNode AI Each project tackles a different bottleneck in the AI economy — data, forecasting, and infrastructure — but they all share the same vision: decentralization, community ownership, and sustainable value creation. Let’s take a deeper look 👇 🧠 Perceptron Network The world’s first community-powered AI data engine Perceptron Network is redefining how AI data is sourced, validated, and delivered. Instead of relying on expensive, closed, and slow legacy data providers, Perceptron unlocks community-powered data pipelines that are: Faster Cheaper Revenue-generating from day one This isn’t experimental AI infrastructure — Perceptron already serves real clients with real revenue, proving that decentralized data engines can outperform traditional incumbents. Why Perceptron matters: AI models are only as good as their data Centralized data monopolies slow innovation Communities can produce higher-quality data at scale By aligning contributors, validators, and clients through incentives, Perceptron turns unused human and network potential into a living data engine for AI. Launching on Mindo AI gives Perceptron access to a broader AI-native community — accelerating adoption, partnerships, and ecosystem growth. 🌌 intodotspace The first 10× leveraged prediction market on Solana intodotspace is pushing the boundaries of on-chain prediction markets. Built by the $1.5B UFO team, this platform introduces: 10× leveraged predictions Ultra-fast execution on Solana Deep liquidity and composable market design The market’s confidence is already clear — the project completed a record-breaking raise that was oversubscribed by 1,360%. What makes intodotspace different: Leverage amplifies conviction, not noise On-chain transparency replaces opaque odds Markets become real-time intelligence engines Prediction markets are often called “truth machines.” intodotspace upgrades them into high-signal, high-efficiency forecasting layers — useful for traders, protocols, DAOs, and even AI systems that need probabilistic insights. Launching on positions intodotspace at the intersection of AI-driven decision-making and on-chain market intelligence. 🌐 DeepNode AI Infrastructure for open intelligence DeepNode AI is tackling one of the biggest problems in modern AI: centralized ownership. Today, AI is dominated by a handful of corporations. DeepNode flips that model by building open intelligence infrastructure where: Anyone can deploy AI models Builders earn directly from usage Intelligence is co-owned, not extracted Backed by leading validators, miners, and ecosystem builders, DeepNode transforms AI from a closed monopoly into a shared utility. DeepNode’s core philosophy: “Own what you build — or someone else will.” This is more than infrastructure. It’s an economic redesign of AI itself: Builders keep ownership Contributors share upside Networks replace platforms Launching on connects DeepNode to creators, researchers, and communities who believe intelligence should belong to everyone — not just Big Tech. 🤝 Why This Matters for With the launch of Perceptron Network, intodotspace, and DeepNode AI, #MindoAI is rapidly becoming: A hub for AI-native Web3 innovation A launchpad for real, revenue-backed projects A meeting point for data, markets, and intelligence infrastructure These three projects don’t compete — they complement each other: Perceptron supplies data intodotspace produces market intelligence DeepNode powers open AI execution Together, they form the backbone of a decentralized intelligence economy. 🔥 The future of AI is open, composable, and community-owned — and it’s launching now on Which of these projects are you most excited about? And how do you see decentralized intelligence reshaping the next AI cycle? 👇 Share your thoughts and join the conversation.

🚀 Three Next-Gen AI & Web3 Projects Are Launching on Mindo AI A new chapter for community-powered intelligence, prediction markets, and open AI infrastructure The AI + Web3 landscape is entering a decisive phase — one where real usage, real revenue, and real ownership matter more than hype. Today, MindoAI is proud to welcome three groundbreaking projects that represent this shift clearly and powerfully: Perceptron Network Space DeepNode AI Each project tackles a different bottleneck in the AI economy — data, forecasting, and infrastructure — but they all share the same vision: decentralization, community ownership, and sustainable value creation. Let’s take a deeper look 👇 🧠 Perceptron Network The world’s first community-powered AI data engine Perceptron Network is redefining how AI data is sourced, validated, and delivered. Instead of relying on expensive, closed, and slow legacy data providers, Perceptron unlocks community-powered data pipelines that are: Faster Cheaper Revenue-generating from day one This isn’t experimental AI infrastructure — Perceptron already serves real clients with real revenue, proving that decentralized data engines can outperform traditional incumbents. Why Perceptron matters: AI models are only as good as their data Centralized data monopolies slow innovation Communities can produce higher-quality data at scale By aligning contributors, validators, and clients through incentives, Perceptron turns unused human and network potential into a living data engine for AI. Launching on Mindo AI gives Perceptron access to a broader AI-native community — accelerating adoption, partnerships, and ecosystem growth. 🌌 intodotspace The first 10× leveraged prediction market on Solana intodotspace is pushing the boundaries of on-chain prediction markets. Built by the $1.5B UFO team, this platform introduces: 10× leveraged predictions Ultra-fast execution on Solana Deep liquidity and composable market design The market’s confidence is already clear — the project completed a record-breaking raise that was oversubscribed by 1,360%. What makes intodotspace different: Leverage amplifies conviction, not noise On-chain transparency replaces opaque odds Markets become real-time intelligence engines Prediction markets are often called “truth machines.” intodotspace upgrades them into high-signal, high-efficiency forecasting layers — useful for traders, protocols, DAOs, and even AI systems that need probabilistic insights. Launching on positions intodotspace at the intersection of AI-driven decision-making and on-chain market intelligence. 🌐 DeepNode AI Infrastructure for open intelligence DeepNode AI is tackling one of the biggest problems in modern AI: centralized ownership. Today, AI is dominated by a handful of corporations. DeepNode flips that model by building open intelligence infrastructure where: Anyone can deploy AI models Builders earn directly from usage Intelligence is co-owned, not extracted Backed by leading validators, miners, and ecosystem builders, DeepNode transforms AI from a closed monopoly into a shared utility. DeepNode’s core philosophy: “Own what you build — or someone else will.” This is more than infrastructure. It’s an economic redesign of AI itself: Builders keep ownership Contributors share upside Networks replace platforms Launching on connects DeepNode to creators, researchers, and communities who believe intelligence should belong to everyone — not just Big Tech. 🤝 Why This Matters for With the launch of Perceptron Network, intodotspace, and DeepNode AI, #MindoAI is rapidly becoming: A hub for AI-native Web3 innovation A launchpad for real, revenue-backed projects A meeting point for data, markets, and intelligence infrastructure These three projects don’t compete — they complement each other: Perceptron supplies data intodotspace produces market intelligence DeepNode powers open AI execution Together, they form the backbone of a decentralized intelligence economy. 🔥 The future of AI is open, composable, and community-owned — and it’s launching now on Which of these projects are you most excited about? And how do you see decentralized intelligence reshaping the next AI cycle? 👇 Share your thoughts and join the conversation.

Hồng Ngọc | Ruby💎

12,837 次观看 • 5 个月前

I just learned something that should terrify every AI investor: Six major large language models were tested on real freelance work - the kind actual humans get paid to do on Upwork. Not homework. Not summaries. Real commercial tasks that generate real revenue. Building video games. Creating presentations from rough notes. Architectural schematics. The BEST performing AI completed tasks well enough to get paid 2.5% of the time. The worst? 0.3%. Think about that. If you were an Uber driver who completed 2.5% of your rides, you'd be kicked off the platform in a week. This comes from academic research published in the Remote Labor Index - not some anti-AI hit piece. They eliminated jobs requiring physical work or heavy human interaction and focused purely on digital deliverables where AI should theoretically excel. And it failed 97.5% of the time. Meanwhile, US tech companies are spending $380 billion on AI infrastructure in 2025-2026. Data centers using the power of 619 houses per GPU stack. Oracle's shares are now BELOW where they were before announcing their massive OpenAI partnership. Blue Owl Capital (AI infrastructure funder): down 40% Fermi (data center REIT): down 60% The funding markets are already getting more discerning. And we haven't even hit the real reckoning yet. AI is excellent at correlation. But correlation isn't how the world works. It can regurgitate answers to questions it's been trained on. But ask it to actually BUILD something, execute a complex task, or operate in the real world where correlations don't hold? It falls apart. Scam Altman showed Operator - OpenAI's agent that's supposed to act like a CEO's assistant. 19 minutes into the demo, they revealed it worked 34% of the time. On their own metrics. Their own homework. That THEY graded. 34%. And that's in a controlled demo environment. In the real world with actual commercial deliverables it's 2.5%. The capital misallocation is 17 times larger than the dotcom bubble. Nvidia's receivables are up 770% in 33 months (Cisco's were up 140% before they collapsed). Every part of the AI stack is losing money except Nvidia - and they're the ones extending vendor financing to keep the whole thing afloat. This isn't a technology that's "almost there." This is a technology with fundamental architectural limits that can't be overcome by just adding more compute. I sat down with Julian Garran - one of the sharpest macro strategists I know - and he walked through why AI was "built to fail" from day one. The full conversation covers: - Why the economics of data centers guarantee losses - The Cisco 2000 playbook playing out in real time - What happens when the funding dries up - Where smart money is rotating (hint: it's not tech) This is a career-defining inflection point in markets. And most investors are still positioned for a productivity revolution that isn't coming. The full interview is in the comment below.

I just learned something that should terrify every AI investor: Six major large language models were tested on real freelance work - the kind actual humans get paid to do on Upwork. Not homework. Not summaries. Real commercial tasks that generate real revenue. Building video games. Creating presentations from rough notes. Architectural schematics. The BEST performing AI completed tasks well enough to get paid 2.5% of the time. The worst? 0.3%. Think about that. If you were an Uber driver who completed 2.5% of your rides, you'd be kicked off the platform in a week. This comes from academic research published in the Remote Labor Index - not some anti-AI hit piece. They eliminated jobs requiring physical work or heavy human interaction and focused purely on digital deliverables where AI should theoretically excel. And it failed 97.5% of the time. Meanwhile, US tech companies are spending $380 billion on AI infrastructure in 2025-2026. Data centers using the power of 619 houses per GPU stack. Oracle's shares are now BELOW where they were before announcing their massive OpenAI partnership. Blue Owl Capital (AI infrastructure funder): down 40% Fermi (data center REIT): down 60% The funding markets are already getting more discerning. And we haven't even hit the real reckoning yet. AI is excellent at correlation. But correlation isn't how the world works. It can regurgitate answers to questions it's been trained on. But ask it to actually BUILD something, execute a complex task, or operate in the real world where correlations don't hold? It falls apart. Scam Altman showed Operator - OpenAI's agent that's supposed to act like a CEO's assistant. 19 minutes into the demo, they revealed it worked 34% of the time. On their own metrics. Their own homework. That THEY graded. 34%. And that's in a controlled demo environment. In the real world with actual commercial deliverables it's 2.5%. The capital misallocation is 17 times larger than the dotcom bubble. Nvidia's receivables are up 770% in 33 months (Cisco's were up 140% before they collapsed). Every part of the AI stack is losing money except Nvidia - and they're the ones extending vendor financing to keep the whole thing afloat. This isn't a technology that's "almost there." This is a technology with fundamental architectural limits that can't be overcome by just adding more compute. I sat down with Julian Garran - one of the sharpest macro strategists I know - and he walked through why AI was "built to fail" from day one. The full conversation covers: - Why the economics of data centers guarantee losses - The Cisco 2000 playbook playing out in real time - What happens when the funding dries up - Where smart money is rotating (hint: it's not tech) This is a career-defining inflection point in markets. And most investors are still positioned for a productivity revolution that isn't coming. The full interview is in the comment below.

George Noble

561,449 次观看 • 5 个月前